Graphical Neural Network for Error Identification

2. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to store, in the graphical database, the system nodes, the virtual nodes, the updated virtual nodes, the dynamic links between the system nodes and virtual nodes, and the dynamic links between the system nodes and the updated virtual nodes.

3. The computing platform of claim 1, wherein a first system node is an application-to-be-upgraded node and a first virtual node is a corresponding virtual upgraded application node, a second system node is a performance node and a second virtual node is a corresponding virtual performance node, a third system node is a memory node and a third virtual node is a corresponding virtual memory node, and a fourth system node is a central processing unit (CPU) utilization node and a fourth virtual node is a corresponding virtual CPU utilization node.

4. The computing platform of claim 3, wherein a first dynamic link is a link between the application-to-be-upgraded node and the corresponding virtual upgraded application node, a second dynamic link is a link between the performance node and the corresponding virtual performance node, a third dynamic link is a link between the memory node and the corresponding virtual memory node, and a fourth dynamic link is a link between the CPU node and the corresponding virtual CPU node.

6. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to train the AI engine using the system nodes, the virtual nodes, the modified virtual nodes, the dynamic links between the system nodes and virtual nodes, the dynamic links between the system nodes and the updated virtual nodes, and the indication of whether or not the at least one action corrected the at least one error.

7. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to store, in the AI engine, the at least one action to correct the at least one error, and the indication of whether or not the at least one action corrected the at least one error.

8. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to output, to the AI engine, based on identifying that the at least one action did not correct the at least one error, a notification that the at least one action did not correct the at least one error.

9. The computing platform of claim 8, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to send a report comprising the at least one error and the at least one action to correct the at least one error and one or more commands directing a user device to display the report, wherein sending the one or more commands directing the user device to display the report causes the user device to display the report.

10. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to monitor the enterprise system after the sending the one or more commands directing the enterprise system to upgrade the application within the enterprise system and execute the at least one action to correct the at least one error on the enterprise system.

11. The computing platform of claim 1, wherein a real-time state of the enterprise system is transmitted to the computing platform using a communication link.

13. The method of claim 12, further comprising storing, in the graphical database, the system nodes, the virtual nodes, the updated virtual nodes, the dynamic links between the system nodes and virtual nodes, and the dynamic links between the system nodes and the updated virtual nodes.

15. The method of claim 12, further comprising training the AI engine using the system nodes, the virtual nodes, the updated virtual nodes, the dynamic links between the system nodes and virtual nodes, the dynamic links between the system nodes and the updated virtual nodes, and the indication of whether or not the at least one action corrected the at least one error.

16. The method of claim 12, further comprising storing, in the AI engine, the at least one action to correct the at least one error, and the indication of whether or not the at least one action corrected the at least one error.

17. The method of claim 12, further comprising, outputting, to the AI engine, based on determining that the at least one action did not correct the at least one error, a notification that the at least one action did not correct the at least one error.

18. The method of claim 12, further comprising monitoring the enterprise system after the sending the one or more commands directing the enterprise system to upgrade the application within the enterprise system and execute the at least one action to correct the at least one error on the enterprise system.

19. The method of claim 12, further comprising transmitting a real-time state of the enterprise system to a computing platform.